Application of Dynamic Intelligent Simulation Technology in Dance Teaching
Ning Fu, Xia Peng
Digital Signal Processing and Artificial Intelligence for Automatic Learning, Vol. 3, No. 3, 2024.
DOI: https://doi.org/10.6025/dspaial/2024/3/3/97-103
Link: https://www.dline.info/dspai/fulltext/v3n3/dspaiv3n3_3.pdf
Abstract:
This paper is based on the dance movement recognition model of 3D Convolutional
Neural Networks (CNNs) and aims to explore the feasibility of applying intelligent
technology to dance teaching. By investigating the current status of intelligent technology
in dance teaching both domestically and internationally, the advantages of
3D CNNs in dance movement recognition are analyzed. In response to the needfor
dance movement recognition, a model based on 3D CNNs is designed and validated
using the MSRAction3D dataset. The experimental results show that the model
achieves high recognition accuracy in 20 dance movement categories, proving its
potential application in dance teaching. This model can provide dance teachers with
accurate movement recognition and personalized guidance, improving teaching effectiveness.